FastQC is a quality control tool for high throughput sequence data, written by Simon Andrews at the Babraham Institute in Cambridge.

Cutadapt is a tool to find and remove adapter sequences, primers, poly-A tails and other types of unwanted sequence from your high-throughput sequencing reads.DOI: 10.14806/ej.17.1.200.

step assembles R1 and R2 for each PE read and performs initial quality checking. Number of successfully assembled (passing) and un-assembled (failed) reads. Typical samples have <1% of reads failing.

assess the quality of the assembly (from the last step) and remove reads that fail (with one or more expected errors, based on combined phred scores of the entire read). Shows the number of total reads and removed reads. Typical samples have <0.1% of reads failing.

step extracts unique sequences for all reads in each sample. Every read count after this step is in terms of unique sequences. Showing the number of total reads and the unique reads. A ratio of 5 or larger typically indicates a good mean read depth for this sample.

step removes unique reads with likely sequencing errors inferred from read frequency and sequence composition. Shows the number of total and removed unique sequences. It is normal for most unique sequences to be removed as most of the remaining reads have high read frequency hence only a small percentage of total (non-unique) reads were removed.

reads count report per primer pair across all samples in this run.

Average, minimum, and maximum read count per primer pair across all samples in the run, with a low(<30x) average read count (<30x red; 30x~50x yellow; >50x green) indicating bad primer performance .